MétaCan
Menu
Back to cohort
Record W2541207084 · doi:10.5539/jpl.v9n9p77

Iran's Political Stance toward Yemen's Ansar Allah Movement: A Constructivist-Based Study

2016· article· en· W2541207084 on OpenAlexvenueno aff
Keyhan Barzegar, Seyyed Morteza Kazemi Dinan

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsIslamPoliticsIslamic republicPolitical scienceState (computer science)Identity (music)SociologyHistoryLawPhilosophyAesthetics

Abstract

fetched live from OpenAlex

In recent years, the role of non-state political groups, particularly in the Middle East has become more prominent. Islamic Republic of Iran has to have a policy toward such groups. One of these groups is Yemen's Ansar Allah who, after the outbreak of protests in the country since 2011, has had a high and effective role in the political arena of Yemen. In this study, based on Constructivist theory of international relations, we attempted to answer this fundamental question that “what is the strategy of Islamic Republic of Iran toward Yemen's Ansar Allah?” Islamic Republic of Iran with regard to the definition of their identity and perceptions of the structure of the international system and the behavior of important regional and international actors as well as their opinions about Ansar Allah Movement as a Shiite, popular, anti-Israel, anti-American, and anti- Saudi group aligned with the values and principles of Islamic Republic System, has taken a supportive stance. Iran's support for Yemen's Ansar Allah is political, diplomatic, media and if possible, material supports (e.g. sending foods and medicine).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.304
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Politics and LawSame topicMiddle East and Rwanda ConflictsFrench-language works237,207